Most wearable robots such as exoskeletons and prostheses can operate with dexterity,
while wearers do not perceive them as part of their bodies. In this perspective, we contend …

Objective. Processing strategies are analyzed with respect to the classification of
electroencephalographic signals related to brain-computer interfaces (BCIs) based on motor …

Neuroprostheses have the potential to restore communication to people who cannot speak
or type due to paralysis. However, it is unclear if silent attempts to speak can be used to …

Brain–computer interfaces are used for direct two-way communication between the human
brain and the computer. Brain signals contain valuable information about the mental state …

The main purpose of this paper is to provide information on how to create a convolutional
neural network (CNN) for extracting features from EEG signals. Our task was to understand …

A virtual world has now become a reality as augmented reality (AR) and virtual reality (VR)
technology become commercially available. Similar to how humans interact with the …

In recent decades, the automatic recognition and interpretation of brain waves acquired by
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …

Brain-computer interface (BCI) technologies have developed as a game changer, altering
how humans interact with computers and opening up new avenues for understanding and …

Brain–computer interfaces (BCIs) are a new technology that subverts traditional human–
computer interaction, where the control signal source comes directly from the user's brain …

The Relevance Feedback (RF) process relies on accurate and real-time relevance
estimation of feedback documents to improve retrieval performance. Since collecting explicit …